Search Results for author: Ying Xu

Found 20 papers, 0 papers with code

An optimised deep spiking neural network architecture without gradients

no code implementations27 Sep 2021 Yeshwanth Bethi, Ying Xu, Gregory Cohen, Andre van Schaik, Saeed Afshar

Through the use of simple local adaptive selection thresholds at each node, the network rapidly learns to appropriately allocate its neuronal resources at each layer for any given problem without using a real-valued error measure.

UIBert: Learning Generic Multimodal Representations for UI Understanding

no code implementations29 Jul 2021 Chongyang Bai, Xiaoxue Zang, Ying Xu, Srinivas Sunkara, Abhinav Rastogi, Jindong Chen, Blaise Aguera y Arcas

Our key intuition is that the heterogeneous features in a UI are self-aligned, i. e., the image and text features of UI components, are predictive of each other.

Multimodal Icon Annotation For Mobile Applications

no code implementations9 Jul 2021 Xiaoxue Zang, Ying Xu, Jindong Chen

Annotating user interfaces (UIs) that involves localization and classification of meaningful UI elements on a screen is a critical step for many mobile applications such as screen readers and voice control of devices.

Object Classification Object Detection

Voltage Inference for and Coordination of Distributed Voltage Controls in Extremely-High DER-Penetration Distribution Networks

no code implementations20 Jan 2021 Ying Xu, Zhihua Qu

The unique problems and phenomena in the distributed voltage control of large-scale power distribution systems with extremely-high DER-penetration are targeted in this paper.

Understanding in Artificial Intelligence

no code implementations17 Jan 2021 Stefan Maetschke, David Martinez Iraola, Pieter Barnard, Elaheh ShafieiBavani, Peter Zhong, Ying Xu, Antonio Jimeno Yepes

A question remains of how much understanding is leveraged by these methods and how appropriate are the current benchmarks to measure understanding capabilities.

Language understanding Natural Language Understanding +2

ActionBert: Leveraging User Actions for Semantic Understanding of User Interfaces

no code implementations22 Dec 2020 Zecheng He, Srinivas Sunkara, Xiaoxue Zang, Ying Xu, Lijuan Liu, Nevan Wichers, Gabriel Schubiner, Ruby Lee, Jindong Chen, Blaise Agüera y Arcas

Our methodology is designed to leverage visual, linguistic and domain-specific features in user interaction traces to pre-train generic feature representations of UIs and their components.

GraphFederator: Federated Visual Analysis for Multi-party Graphs

no code implementations27 Aug 2020 Dongming Han, Wei Chen, Rusheng Pan, Yijing Liu, Jiehui Zhou, Ying Xu, Tianye Zhang, Changjie Fan, Jianrong Tao, Xiaolong, Zhang

This paper presents GraphFederator, a novel approach to construct joint representations of multi-party graphs and supports privacy-preserving visual analysis of graphs.

Human-Computer Interaction Cryptography and Security Graphics

Estimating the Number of Infected Cases in COVID-19 Pandemic

no code implementations24 May 2020 Donghui Yan, Ying Xu, Pei Wang

We propose a structured approach for the estimation of the number of unreported cases, where we distinguish cases that arrive late in the reported numbers and those who had mild or no symptoms and thus were not captured by any medical system at all.

Elephant in the Room: An Evaluation Framework for Assessing Adversarial Examples in NLP

no code implementations22 Jan 2020 Ying Xu, Xu Zhong, Antonio Jose Jimeno Yepes, Jey Han Lau

An adversarial example is an input transformed by small perturbations that machine learning models consistently misclassify.

Similarity Kernel and Clustering via Random Projection Forests

no code implementations28 Aug 2019 Donghui Yan, Songxiang Gu, Ying Xu, Zhiwei Qin

Similarity plays a fundamental role in many areas, including data mining, machine learning, statistics and various applied domains.

Clustering Ensemble

Learning over inherently distributed data

no code implementations30 Jul 2019 Donghui Yan, Ying Xu

This framework only requires a small amount of local signatures to be shared among distributed sites, eliminating the need of having to transmitting big data.

Distributed Computing

Event-based Feature Extraction Using Adaptive Selection Thresholds

no code implementations18 Jul 2019 Saeed Afshar, Ying Xu, Jonathan Tapson, André van Schaik, Gregory Cohen

A novel heuristic method for network size selection is proposed which makes use of noise events and their feature representations.

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